Currently, in comparison with an image obtained by means of conventional photographing, multiple frames of LDR (Low Dynamic Range, low dynamic range imaging) images having different exposure are synthesized by using an HDR (High Dynamic Range, high dynamic range imaging) image, so that a wider dynamic range and more image details can be provided, and a visual effect in a real environment can be better reflected. Therefore, this technology is widely applied to a Camera photographing field of a smart terminal.
Because multiple frames of images having different exposure need to be captured in an HDR technology, and due to a limitation of a maximum frame rate of a Camera photographing system, there is a photographing time interval between these multiple frames of images. Within the time interval, if a hand trembles or an object in a scene moves, where for example, the wind blows a branch and a person walks, image content in these images change, and a “ghost” phenomenon occurs during image synthesis. Generally, ghost often occurs in a photo, and is most common especially during backlight photographing. In an optical imaging system, one or more images similar to an image point exist around the image point, and other image points except the image point are collectively referred to as “ghost”. For example, in FIG. 1, an image on the right in FIG. 1 is an entity person A during normal photographing, and an image on the left is ghost B that appears. For photographing a fast-moving scene, this phenomenon is especially obvious. Therefore, how to eliminate “ghost” becomes one of difficulties in the HDR technology, and has great importance to quality of an HDR image.
To eliminate “ghost”, the prior art has the following two methods:
Method 1: On a Camera component, different exposure is used for sensing units in alternate rows and/or columns, and then HDR is obtained by using a digital interpolation technology and an image fusion algorithm.
In this solution, a “ghost” problem can be well resolved, but because exposure in alternate rows/columns and digital interpolation are used, image resolution is relatively low.
Method 2: Before the image fusion algorithm is used, an image registration algorithm and a deghosting algorithm are added, so that impact of a hand tremble and a scene motion on image fusion is reduced.
In this solution, the ghost problem can be improved to some degree. However, algorithm complexity is increased, and in some scenarios, the registration algorithm and the deghosting algorithm fail or a mistake is introduced, and “ghost” in the HDR image cannot be well eliminated. As shown in FIG. 2, in addition to the entity person A, the ghost B still exists.
In conclusion, there is still no relatively good method for eliminating “ghost” in an HDR image in the prior art.
Therefore, a technical problem existing in the prior art is that when a hand trembles and/or an object in a scene moves during photographing, a “ghost” phenomenon exists in a high dynamic range image generated by fusing multiple frames of time-division images.